Search results for: models synthesis

Authors: Nikola Toshikj, Michel Ramonda, Sylvain Catrouillet, Jean-Jacques Robin, Sebastien Blanquer

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Biodegradable and biocompatible block copolymers have risen as the golden materials in both medical and environmental applications. Moreover, if their architecture is of controlled manner, higher applications can be foreseen. In the meantime, organocatalytic ROP has been promoted as more rapid and immaculate route, compared to the traditional organometallic catalysis, towards efficient synthesis of block copolymer architectures. Therefore, herein we report novel organocatalytic pathway with guanidine molecules (TBD) for supported synthesis of trimethylene carbonate initiated by poly(caprolactone) as pre-polymer. Pristine PTMC-b-PCL-b-PTMC block copolymer structure, without any residual products and clear desired block proportions, was achieved under 1.5 hours at room temperature and verified by NMR spectroscopies and size-exclusion chromatography. Besides, when elaborating block copolymer films, further stability and amelioration of mechanical properties can be achieved via additional reticulation step of precedently methacrylated block copolymers. Subsequently, stimulated by the insufficient studies on the phase-separation/crystallinity relationship in these semi-crystalline block copolymer systems, their intrinsic thermal and morphology properties were investigated by differential scanning calorimetry and atomic force microscopy. Firstly, by DSC measurements, the block copolymers with χABN values superior to 20 presented two distinct glass transition temperatures, close to the ones of the respecting homopolymers, demonstrating an initial indication of a phase-separated system. In the interim, the existence of the crystalline phase was supported by the presence of melting temperature. As expected, the crystallinity driven phase-separated morphology predominated in the AFM analysis of the block copolymers. Neither crosslinking at melted state, hence creation of a dense polymer network, disturbed the crystallinity phenomena. However, the later revealed as sensible to rapid liquid nitrogen quenching directly from the melted state. Therefore, AFM analysis of liquid nitrogen quenched and crosslinked block copolymer films demonstrated a thermodynamically driven phase-separation clearly predominating over the originally crystalline one. These AFM films remained stable with their morphology unchanged even after 4 months at room temperature. However, as demonstrated by DSC analysis once rising the temperature above the melting temperature of the PCL block, neither the crosslinking nor the liquid nitrogen quenching shattered the semi-crystalline network, while the access to thermodynamical phase-separated structures was possible for temperatures under the poly (caprolactone) melting point. Precisely this coexistence of dual crosslinked/crystalline networks in the same copolymer structure allowed us to establish, for the first time, the shape-memory properties in such materials, as verified by thermomechanical analysis. Moreover, the response temperature to the material original shape depended on the block copolymer emplacement, hence PTMC or PCL as end-block. Therefore, it has been possible to reach a block copolymer with transition temperature around 40°C thus opening potential real-life medical applications. In conclusion, the initial study of phase-separation/crystallinity relationship in PTMC-b-PCL-b-PTMC block copolymers lead to the discovery of novel shape memory materials with superior properties, widely demanded in modern-life applications.

Keywords: biodegradable block copolymers, organocatalytic ROP, self-assembly, shape-memory

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Authors: Lim Chen Kim, Tan Kian Lam, Chan Yi Chee

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This research presents a multi-modal simulation in the reconstruction of the past and the construction of present in digital cultural heritage on mobile platform. In bringing the present life, the virtual environment is generated through a presented scheme for rapid and efficient construction of 360° panoramic view. Then, acoustical heritage model and crowd model are presented and improvised into the 360° panoramic view. For the reconstruction of past life, the crowd is simulated and rendered in an old trading port. However, the keystone of this research is in a virtual walkthrough that shows the virtual present life in 2D and virtual past life in 3D, both in an environment of virtual heritage sites in George Town through mobile device. Firstly, the 2D crowd is modelled and simulated using OpenGL ES 1.1 on mobile platform. The 2D crowd is used to portray the present life in 360° panoramic view of a virtual heritage environment based on the extension of Newtonian Laws. Secondly, the 2D crowd is animated and rendered into 3D with improved variety and incorporated into the virtual past life using Unity3D Game Engine. The behaviours of the 3D models are then simulated based on the enhancement of the classical model of Boid algorithm. Finally, a demonstration system is developed and integrated with the models, techniques and algorithms of this research. The virtual walkthrough is demonstrated to a group of respondents and is evaluated through the user-centred evaluation by navigating around the demonstration system. The results of the evaluation based on the questionnaires have shown that the presented virtual walkthrough has been successfully deployed through a multi-modal simulation and such a virtual walkthrough would be particularly useful in a virtual tour and virtual museum applications.

Keywords: Boid Algorithm, Crowd Simulation, Mobile Platform, Newtonian Laws, Virtual Heritage

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Authors: Young Min Kim, Deokyeong Choe, Chul Soo Shin

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Monascus pigments, commonly used as a natural colorant in Asia, have many biological activities, such as cholesterol level control, anti-obesity, anti-cancer, and anti-oxidant, that have recently been elucidated. Especially, amino acid derivatives of Monascus pigments are receiving much attention because they have higher biological activities than original Monascus pigments. Previously, there have been two ways to produce amino acid derivatives: one-step production and two-step production. However, the one-step production has low purity, and the two-step production—precursor(orange pigments) fermentation and derivatives synthesis—has low productivity and growth rate during its precursor fermentation step. In this study, it was verified that pH is a key factor that affects the stability of orange pigments and the growth rate of Monascus. With an optimal pH profile obtained by pH-stat fermentation, we designed a process of precursor(orange pigments) fermentation that is a pH-controlled fed-batch fermentation. The final concentration of orange pigments in this process increased to 5.5g/L which is about 30% higher than the concentration produced from the previously used precursor fermentation step.

Keywords: cultivation process, fed-batch fermentation, monascus pigments, pH stability

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Authors: Z. B. Ibrahim, N. Ismail, K. I. Othman

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Fuzzy Differential Equations (FDEs) play an important role in modelling many real life phenomena. The FDEs are used to model the behaviour of the problems that are subjected to uncertainty, vague or imprecise information that constantly arise in mathematical models in various branches of science and engineering. These uncertainties have to be taken into account in order to obtain a more realistic model and many of these models are often difficult and sometimes impossible to obtain the analytic solutions. Thus, many authors have attempted to extend or modified the existing numerical methods developed for solving Ordinary Differential Equations (ODEs) into fuzzy version in order to suit for solving the FDEs. Therefore, in this paper, we proposed the development of a fuzzy version of three-point block method based on Block Backward Differentiation Formulas (FBBDF) for the numerical solution of first order FDEs. The three-point block FBBDF method are implemented in uniform step size produces three new approximations simultaneously at each integration step using the same back values. Newton iteration of the FBBDF is formulated and the implementation is based on the predictor and corrector formulas in the PECE mode. For greater efficiency of the block method, the coefficients of the FBBDF are stored at the start of the program. The proposed FBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing fuzzy version of the Modified Simpson and Euler methods in terms of the accuracy of the approximated solutions. The numerical results show that the FBBDF method performs better in terms of accuracy when compared to the Euler method when solving the FDEs.

Keywords: block, backward differentiation formulas, first order, fuzzy differential equations

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Authors: Kamel Malik Bensafta, Gervasio Bensafta

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: Srinivasa Reddy Mallampati, Byoung Ho Lee, Yoshiharu Mitoma, Simion Cristian

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In recent years, environmental nanotechnology has risen to the forefront and the new properties and enhanced reactivates offered by nanomaterial may offer a new, low-cost paradigm to solving complex environmental pollution problems. This study assessed the synthesis and application of multi-functioned nano-size metallic calcium (nMC) composite for detoxification of hazardous inorganic (heavy metals (HMs)/organic chlorinated/brominated compound (CBCs) contaminants in automobile shredder residue (ASR). ASR residues ball milled with nMC composite can achieve about 90-100% of HMs immobilization and CBCs decomposition. The results highlight the low quantity of HMs leached from ASR residues after treatment with nMC, which was found to be lower than the standard regulatory limit for hazardous waste landfills. The use of nMC composite in a mechanochemical process to treat hazardous ASR (dry conditions) is a simple and innovative approach to remediate hazardous inorganic/organic cross-contaminates in ASR.

Keywords: nano-sized metallic calcium, automobile shredder residue, organic/inorganic contaminants, immobilization, detoxification

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Authors: B. Kahouadji, L. Guerbous, L. Lamiri, A. Mendoud

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Recently, nanomaterials are developed in the form of nano-films, nano-crystals and nano-pores. Lanthanide phosphates as a material find extensive application as laser, ceramic, sensor, phosphor, and also in optoelectronics, medical and biological labels, solar cells and light sources. Among the different kinds of rare-earth orthophosphates, yttrium orthophosphate has been shown to be an efficient host lattice for rare earth activator ions, which have become a research focus because of their important role in the field of light display systems, lasers, and optoelectronic devices. It is in this context that the 4fn- « 4fn-1 5d transitions of rare earth in insulating materials, lying in the UV and VUV, are the aim of large number of studies .Though there has been a few reports on Eu3+, Nd3+, Pr3+,Er3+, Ce3+, Tm3+ doped YPO4. The 4fn- « 4fn-1 5d transitions of the rare earth dependent to the host-matrix, several matrices ions were used to study these transitions, in this work we are suggesting to study on a very specific class of inorganic material that are orthophosphate doped with rare earth ions. This study focused on the effect of Ce3+ concentration on the structural and optical properties of Ce3+ doped YPO4 yttrium orthophosphate with powder form prepared by the Sol Gel method.

Keywords: YPO4, Ce3+, 4fn- <->4fn-1 5d transitions, scintillator

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Authors: Iram Batool, Aamer Saeed, Irfan Zia Qureshi, Ayesha Razzaq, Saima Kalsoom

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Heterocyclic compounds analogues and their derivatives have attracted strong interest in medicinal chemistry due to their biological and pharmacological properties. A series of new thiazolopyrimidine carboxylates were conveniently synthesized by one-pot three-component reaction of ethyl acetoacetate, 2-aminothiazole and benzaldehyde substituted with electron-donating and electron-withdrawing groups in order to find some more potent antidiabetic and antibacterial drugs. The structures of synthesized compounds were characterized by elemental analysis, IR, 1H NMR, 13C NMR spectroscopy. An in vitro antidiabetic effect was evaluated in adult male BALB/c mice and antibacterial activities were tested against Micrococcus luteus, Salmonella typhimurium, Bacillus subtilis, Bordetella bronchiseptica and Escherichia coli. Some of the tested compounds proved to possess good to excellent activities more than the reference drugs. An in silico molecular docking was also performed on synthesized compounds. The current study is expected to provide useful insights into the design of antidiabetic and antibacterial drugs and understanding the mechanism by which such drugs interact with RNA and diabetes target and exert their biochemical action.

Keywords: antidiabetic, antibacterial, MOE docking, thiazolopyrimidine

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Authors: Yousef Bakhbakhi

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Crystallization with supercritical fluids (SCFs), as a developed technology to produce particles of micron and sub-micron size with narrow size distribution, has found appreciable importance as an environmentally friendly technology. Particle synthesis using SCFs can be achieved employing a number of special processes involving solvent and antisolvent mechanisms. In this study, the compressed antisolvent (PCA) process is utilized as a model to analyze the theoretical complexity of crystallization with supercritical fluids. The population balance approach has proven to be an effectual technique to simulate and predict the particle size and size distribution. The nucleation and growth mechanisms of the particles formation in the PCA process is investigated using the population balance equation, which describes the evolution of the particle through coalescence and breakup levels with time. The employed mathematical population balance model contains a set of the partial differential equation with algebraic constraints, which demands a rigorous numerical approach. The combined Collocation and Galerkin finite element method are proposed as a high-resolution technique to solve the dynamics of the PCA process.

Keywords: particle formation, particle size and size distribution, PCA, supercritical carbon dioxide

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Authors: Satya Eswari Jujjavarapu, Swasti Dhagat, Lata Upadhyay, Reecha Sahu

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Silver nanoparticles have a broad range of antimicrobial and antifungal properties ranging from soaps, pastes to sterilization and drug delivery systems. These can be synthesized by physical, chemical and biological methods; biological methods being the most popular owing to their non-toxic nature and reduced energy requirements. Microbial surfactants, produced on the microbial cell surface or excreted extracellularly are an alternative to synthetic surfactants for the production of silver nanoparticles. Hence, they are also called as green molecules. Microbial lipopeptide surfactants (biosurfactant) exhibit anti-tumor and anti-microbial properties and can be used as drug delivery agents. In this study, biosurfactant was synthesized by using a strain of acillus subtilis. The biosurfactant thus produced was analysed by emulsification assay, oil spilling test, and haemolytic test. Biosurfactant-mediated silver nanoparticles were synthesised by microwave irradiation of the culture supernatant and further characterized by UV–vis spectroscopy for a range of 400-600 nm. The UV–vis spectra showed a surface plasmon resonance vibration band at 410 nm corresponding to the peak of silver nanoparticles.

Keywords: biosurfactant, Bacillus subtilis, silver nano particle, lipopeptide

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Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić

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Prion is a protein substance whose certain form is considered as infectious agent. It is presumed to be the cause of the transmissible spongiform encephalopathies (TSEs). The protein it is composed of, called PrP, can fold in structurally distinct ways. At least one of those 3D structures is transmissible to other prion proteins. Prions can be found in brain tissue of healthy people and have certain biological role. The structure of prions naturally occurring in healthy organisms is marked as PrPc, and the structure of infectious prion is labeled as PrPSc. PrPc may play a role in synaptic plasticity and neuronal development. Also, it may be required for neuronal myelin sheath maintenance, including a role in iron uptake and iron homeostasis. PrPSc can be considered as an environmental pollutant. The main aim of this study was to carry out the molecular modeling and calculation of molecular descriptors (lipophilicity, physico-chemical and topological descriptors) of structurally diverse compounds which can be considered as anti-prion agents. Molecular modeling was conducted applying ChemBio3D Ultra version 12.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The Austin Model 1 (AM-1) was used for full geometry optimization of all structures. The obtained set of molecular descriptors is applied in analysis of similarities and dissimilarities among the tested compounds. This study is an important step in further development of quantitative structure-activity relationship (QSAR) models, which can be used for prediction of anti-prion activity of newly synthesized compounds.

Keywords: chemometrics, molecular modeling, molecular descriptors, prions, QSAR

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Authors: Hassiba Bougueria, Nesrine Benarous, Souheyla Chetioui

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Azo dyes are one of the most widely used compounds in organic chemistry, primarily due to their relatively simple preparation methods. They have therefore been widely used, in particular as colorants for textiles, printing inks, cosmetics, and food additives. In addition to their use as dyes, azo compounds have attracted much attention from chemists as their potential applications are important in coordination chemistry, metal-organic frameworks (MOF) structures, COF (covalent-organic frameworks), and catalysis. Moreover, they have found many applications in different fields, such as nonlinear optics, optical storage, photoluminescence, and magnetism. The compound bis{(E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalen-2-olato}copper(II) dimethyl sulfoxide monosolvate, the CuII atom is tetracoordinate with a square-planar geometry, surrounded by two bidentate (E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalene-2-olate ligands via two N atoms and two O atoms. The O-Cu-O angles and N-Cu-N are of the order of 177.90(16)° and 177.8(2)°, respectively. The distances Cu-O and Cu- N are 1.892(4) Å and 1.976(4) Å, respectively. The cohesion of the crystal is ensured by hydrogen bonds of the C—H…O type and by π=π staking interactions [centroid–centroid distance = 3.679(4)Å]. The DMSO solvent molecule is disordered at two positions with occupancy rates of 0.70 and 0.30.

Keywords: azo dyes, DRX, structural characterization, biological activity

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Authors: Mohammadjavad Sotoudeheian, Navid Farahmandian

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Kawasaki disease (KD) is the primary cause of acquired pediatric heart disease as an acute vasculitis. In children with prolonged fever, rash, and inflammation of the mucosa KD must be considered as a clinical diagnosis. There is a persuasive suggestion of immune-mediated damage as the pathophysiologic cascade of KD. For example, the invasion of cytotoxic T-cells supports a viral etiology and the inflammasome of the innate immune system is a critical component in the vasculitis formation in KD. Animal models of KD propose the cytokine profiles, such as increased IL-1 and GM-CSF, which cause vascular damage. CRP and IFN-γ elevated expression and the upregulation of IL-6, and IL-10 production are also described in previous studies. Untreated KD is a critical risk factor for coronary artery diseases and myocardial infarction. Vascular damage may encompass amplified T-cell activity. SMAD3 is an essential molecule in down-regulating T-cells and increasing expression of FoxP3. It has a critical effect in the differentiation of regulatory T-cells. The discrepancy of regulatory T-cells and pro-inflammatory Th17 has been studied in acute coronary syndrome during KD. However in the coronary artery damaged lymphocytes and IgA plasma cells are seen at the lesion locations, the major immune cells in the coronary lesions are monocytes/macrophages and neutrophils. These cells secrete TNF-α, and activates matrix metalloprotease (MMP)-9, reducing the integrity of vessels and prompting patients to arise aneurysm. MMPs can break down the components of the extracellular matrix and assist immune cell movement. IVIG as an effective form of treatment clarified the role of the immune system, which may target pathogenic antigens and regulate cytokine production. Several reports have revealed that in the coronary arteries, high expression of MMP-9 in monocyte/macrophage results in pathologic cascades. Curcumin is a potent antioxidant and anti-inflammatory molecule. Curcumin decreases the production of reactive oxygen and nitrogen species and inhibits transcription factors like AP-1 and NF-κB. Curcumin also contains the characteristics of inhibitory effects on MMPs, especially MMP-9. The upregulation of MMP-9 is an important cellular response. Curcumin treatment caused a reverse effect and down-regulates MMP-9 gene expression which may fund the anti-inflammatory effect. Curcumin inhibits MMP-9 expression via PKC and AMPK-dependent pathways in Human monocytes cells. Elevated expression and activity of MMP-9 are correlated with advanced vascular lesions. AMPK controls lipid metabolism and oxidation, and protein synthesis. AMPK is also necessary for the MMP-9 activity and THP-1 cell adhesion to endothelial cells. Curcumin was shown to inhibit the activation of AMPKα. Compound C (AMPK inhibitor) inhibits MMP-9 expression level. Therefore, through inactivating AMPKs and PKC, curcumin decreases the MMP-9 level, which results in inhibiting monocyte/macrophage differentiation. Compound C also suppress the phosphorylation of three major classes of MAP kinase signaling, suggesting that curcumin may suppress MMP-9 level by inactivation of MAPK pathways. MAPK cascades are activated to induce the expression of MMP-9. Curcumin inhibits MAPKs phosphorylation, which contributes to the down-regulation of MMP-9. This study demonstrated that the potential inhibitory properties of curcumin over MMP-9 lead to a therapeutic strategy to reduce the risk of coronary artery involvement during KD.

Keywords: MMP-9, coronary artery aneurysm, Kawasaki’s disease, curcumin, AMPK, immune system, NF-κB, MAPK

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Authors: Radka Králová, Libor Kvítek, Václav Ranc, Aleš Panáček, Radek Zbořil

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Surface–Enhanced Raman Scattering (SERS) is an optical spectroscopic technique with very good potential for sensitive detection of substances. In this research, active substrates with high enhancement were provided. Novel silver particles (nanostructures) with high roughened, flower–like morphology were prepared by reduction of cation complex [Ag(NH3)2]+ in presence of sodium borohydride as reducing agent and stabilized polyacrylic acid. The products were characterized by UV/VIS absorption spectrophotometry. Special shapes of silver particles were determined by scanning electron microscopy (SEM) and transmission electron spectroscopy (TEM). Dispersions of this particle were put on fixed substrate to producing suitable layer for SERS. Adenine was applied as basic substance whose effect of enhancement on the layer of silver nanostructures was studied. By comparison with our work, the important influence of stabilizers, polyacrylic acid with various molecular weight and concentration, on the transfer of particles and formation of new structure was confirmed.

Keywords: metals, nanostructures, chemical reduction, Raman spectroscopy, optical properties

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Authors: Nguyen Chi Quang, Nguyen Duong Tri Nguyen

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This article is the first step to research and outline the structure of the geotechnical database in the geological survey of a power project; in the context of this report creating the database that has been carried out for the Bac Ai pumped storage hydropower project. For the purpose of providing a method of organizing and storing geological and topographic survey data and experimental results in a spatial database, the RockWorks software is used to bring optimal efficiency in the process of exploiting, using, and analyzing data in service of the design work in the power engineering consulting. Three-dimensional (3D) geotechnical models are created from the survey data: such as stratigraphy, lithology, porosity, etc. The results of the 3D geotechnical model in the case of Bac Ai pumped storage hydropower project include six closely stacked stratigraphic formations by Horizons method, whereas modeling of engineering geological parameters is performed by geostatistical methods. The accuracy and reliability assessments are tested through error statistics, empirical evaluation, and expert methods. The three-dimensional model analysis allows better visualization of volumetric calculations, excavation and backfilling of the lake area, tunneling of power pipelines, and calculation of on-site construction material reserves. In general, the application of engineering geological modeling makes the design work more intuitive and comprehensive, helping construction designers better identify and offer the most optimal design solutions for the project. The database always ensures the update and synchronization, as well as enables 3D modeling of geological and topographic data to integrate with the designed data according to the building information modeling. This is also the base platform for BIM & GIS integration.

Keywords: database, engineering geology, 3D Model, RockWorks, Bac Ai pumped storage hydropower project

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Authors: Suvorov Vasyl, Filipchuk Viktor

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Developmental Dysplasia of the Hip (DDH) is a frequent pathology in pediatric orthopedist’s practice. Neglected or residual cases of DDH in walking patients are usually treated using pelvic osteotomies. Plastic changes take place in hinge points due to acetabulum reorientation during surgery. Classically described hinge points and a traditional division of pelvic osteotomies on reshaping and reorientation are currently debated. The purpose of this article was to evaluate biomechanical changes during the most commonly used pelvic osteotomies (Salter, Dega, Pemberton) for DDH treatment in pediatric patients. Methods: virtual pelvic models of 2- and 6-years old patients were created, material properties were assigned, pelvic osteotomies were simulated and biomechanical changes were evaluated using finite element analysis (FEA). Results: it was revealed that the patient's age has an impact on pelvic bones and cartilages density (in younger patients the pelvic elements are more pliable - p<0.05). Stress distribution after each of the abovementioned pelvic osteotomy was assessed in 2- and 6-years old patients’ pelvic models; hinge points were evaluated. The new term "restriction point" was introduced, which means a place where restriction of acetabular deformity correction occurs. Pelvic ligaments attachment points were mainly these restriction points. Conclusions: it was found out that there are no purely reshaping and reorientation pelvic osteotomies as previously believed; the pelvic ring acts as a unit in carrying out the applied load. Biomechanical overload of triradiate cartilage during Salter osteotomy in 2-years old patient and in 2- and 6-years old patients during Pemberton osteotomy was revealed; overload of the posterior cortical layer in the greater sciatic notch in 2-years old patient during Dega osteotomy was revealed. Level of Evidence – Level IV, prognostic.

Keywords: developmental dysplasia of the hip, pelvic osteotomy, finite element analysis, hinge point, biomechanics

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Authors: Drashti G. Daraji, Rosa E. Moo-Puc, Hitesh D. Patel

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Substituted 2-Thioimidazole analogues have been synthesized and confirmed by advanced spectroscopic techniques. Among them, ten compounds have been selected and evaluated for their in vitro anti-cancer activity at the National Cancer Institute (NCI) for testing against a panel of 60 different human tumor cell lines derived from nine neoplastic cancer types. Furthermore, synthesized compounds were tested for their in vitro antiprotozoal activity, and none of them exhibited significant potency against antiprotozoans. It was observed that the tested all compounds seem effective on the UACC-62 melanoma cancer cell line as compared to other cancer cell lines and also exhibited the least potent in the Non-Small Cell Lung Cancer cell line in one-dose screening. In silico studies of these derivatives were carried out by molecular docking techniques and Absorption, Distribution, Metabolism, and Excretion (ADME) using Schrödinger software to find potent B-Raf kinase inhibitor (PDB ID: 3OG7). All the compounds have been performed for docking study; Compound D4 has a good docking score for melanoma cancer as compared with other.

Keywords: anticancer activity, cancer cell line, 2-thio imidazole, one-dose assay, molecular docking

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Sebastian Gerber, Julian Fesel, Christian Zimmer, Pauline Yzombard, Daniel Comparat, Michael Doser

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Molecular anions play a central role in a wide range of fields: from atmospheric and interstellar science, anionic superhalogens to the chemistry of highly correlated systems. However, up to now the synthesis of negative ions in a controlled manner at ultracold temperatures, relevant for the processes in which they are involved, is currently limited to a few Kelvin by supersonic beam expansion followed by resistive, buffer gas or electron cooling in cryogenic environments. We present a realistic scheme for laser cooling of C2- molecules to sub-Kelvin temperatures, which has so far only been achieved for a few neutral diatomic molecules. The generation of a pulsed source of C2- and subsequent laser cooling techniques of C2- molecules confined in a Penning trap are reviewed. Further, laser cooling of one anionic species would allow to sympathetically cool other molecular anions, electrons and antiprotons that are confined in the same trapping potential. In this presentation the status of the experiment and the feasibility of C2- sympathetic Doppler laser cooling, photo-detachment cooling and AC-Stark Sisyphus cooling will be reviewed.

Keywords: antiprotons, anions, cooling of ions and molecules, Doppler cooling, photo-detachment, penning trap, Sisyphus cooling, sympathetic cooling

Procedia PDF Downloads 381

Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

Procedia PDF Downloads 332

Authors: Edgar Aguilar-Ortíz, Nicolas Lévaray, Mireille Vonlanthen, Eric G. Morales-Espinoza, Ernesto Rivera, Xiao Xia Zhu

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Four new star compounds bearing a porphyrin core and cholic acid units, (TPPh(Zn) tetra-CA, TPPh(2H) tetra-CA, TPPh(Zn) octa-CA and TPPh(2H) octa-CA), have been synthesized using the Click Chemistry approach, which consist on azide-alkyne couplings. These novel functionalized porphyrins were characterized by 1H and 13C NMR spectroscopy and their structure was confirmed by MALDI-TOF. The optical properties of these compounds were studied by absorption and fluorescence spectroscopy. On the other hand, order to evaluate the amphiphilic properties of the cholic acid units combined with the optical response of the porphyrin core, we performed absorption and fluorescence studies in function of the polarity of the environment. It was found that as soon as we increase the polarity of the solvent, the Zn-metallated porphyrins, (TPPh(Zn) tetra-CA and TPPh(Zn) octa-CA), are able to form J aggregates, whereas the free-base porphyrins, TPPh(2H) tetra-CA and TPPh(2H) octa-CA, behaved differently.

Keywords: aggregates, amphiphilic, cholic acid, click-chemistry, porphyrin

Procedia PDF Downloads 307

Authors: Pimchanok Puksisuwan, Pitak Laorattanakul, Benya Cherdhirunkorn

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The use of aluminium dross as a raw material for geopolymer synthesis via mechanochemistry method was studied. The geopolymers were prepared using aluminium dross from secondary aluminium industry, fly ash from a biomass power plant and liquid alkaline activators, which is a mixture of sodium silicate solution (Na2SiO3) and sodium hydroxide solution (NaOH) (Na2SiO3/NaOH ratio 4:1, 3:1 and 2:1). Aluminium dross consists mostly of alumina (Al2O3), silicon oxide (SiO2) and aluminium nitride (AlN). The raw materials were mixed and milled using the high energy ball milling method for 5, 10 and 15 minutes in order to reduce the particle size. The milled powders were uniaxially pressed into a cylinder die with the pressure of 2200 psi. The cylinder samples were cured in the sealed plastic bags for 3, 7 and 14 days at the room temperature and 60°C for 24 hour. The mechanical property of geopolymers was investigated. In addition, scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were carried out in order to study the microstructure and phase structures of the geopolymers, respectively. The results showed that aluminium dross could enhance the mechanical property of geopolymers product by mechanochemistry method and meet the TISI requirements.

Keywords: aluminium dross, fly ash, geopolymer, mechanochemistry

Procedia PDF Downloads 253

Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

Procedia PDF Downloads 428

Authors: M. Sorahi Nobar, V. Niknam, H. Ebrahimzadeh, H. Soltanloo

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Fusarium graminearum is one of the most destructive crop diseases in the world. Infection occurs during the flowering period in warm and humid conditions. It causes reduction in yield. Moreover, harvested grain is often contaminated with mycotoxins and its acetylated derivatives. Fusarium mycotoxines are potent inhibitor of protein synthesis, and thereby presents hazards for both human and animal health. A rapid production of reactive oxygen intermediates, primarily superoxide and hydrogen peroxide at the site of attempted infection considered as key feature underlying successful pathogen recognition. Here, we compared the time course activity of superoxide dismutase (SOD) as a first line of defenses against ROS- induced oxidative burst between FHB- resistant Sumai3 and susceptible Falat at 48, 96 and 144 hours after infection. Our results showed that Sumai3 SOD activity increased with time and reached the highest-level 4 days after infection while in susceptible cultivar Falat, SOD activity decreased during the first 96 h. after infection. Decreased was followed by an increased at 6 days after infection. According to our results rapid induction of SOD activity in resistant cultivar may play an important role in resistance against FHB in wheat.

Keywords: Fusarium graminearum, mycotoxins, resistant cultivar, superoxide dismutase

Procedia PDF Downloads 448

Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

Procedia PDF Downloads 92

Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

Procedia PDF Downloads 157

Authors: Lindie Grebe

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This paper reports on a study that explored the strategizing practices of professional accountants in the mining industry, based on Jarratt and Stiles’ dominant strategizing practice models framework. Drawing on a strategy-as-practice perspective, the paper recognises qualified professional accountants in strategic management such as Chief Executive Officers, as strategy practitioners that perform their strategizing practices and praxis within a specific context. The main findings of this paper were produced through semi-structured individual interviews with accountants that perform strategy on a business level in the South African mining industry. Qualitative data were analysed through conversation analysis over two coding-cycles. Findings describe accountant strategists as practitioners who challenge the dominant business model when a disconnect seems to exist between international corporate level strategy and business level strategy in the South African mining industry. Accountant strategy practitioners described their dominant strategizing practice model as incremental change during strategic planning and as a lived experience during strategy implementation. Findings portrayed these strategists as taking initiative as strategy leaders in a dynamic and volatile environment to combine their accounting background with strategic management and challenge the dominant business model. Understanding how accountant strategists perform strategizing offers insight into the social practice of strategic management. This understanding contributes to the body of knowledge on strategizing in the South African mining industry. In addition, knowledge on the transformation of accountants as strategists could provide valuable practice relevant insights for accounting educators and the accounting profession alike.

Keywords: accountant strategists, dominant strategizing practice models framework, mining industry, strategy-as-practice

Procedia PDF Downloads 175